热稳定性
蛋白质工程
蛋白质设计
计算生物学
工程设计过程
计算机科学
定向进化
定向分子进化
合成生物学
人工智能
生物
蛋白质结构
工程类
突变体
酶
机械工程
基因
生物化学
作者
Ge Qu,Tong Zhu,Yingying Jiang,Bian Wu,Zhoutong Sun
出处
期刊:PubMed
[National Institutes of Health]
日期:2019-10-25
卷期号:35 (10): 1843-1856
被引量:13
标识
DOI:10.13345/j.cjb.190221
摘要
By constructing mutant libraries and utilizing high-throughput screening methods, directed evolution has emerged as the most popular strategy for protein design nowadays. In the past decade, taking advantages of computer performance and algorithms, computer-assisted protein design has rapidly developed and become a powerful method of protein engineering. Based on the simulation of protein structure and calculation of energy function, computational design can alter the substrate specificity and improve the thermostability of enzymes, as well as de novo design of artificial enzymes with expected functions. Recently, machine learning and other artificial intelligence technologies have also been applied to computational protein engineering, resulting in a series of remarkable applications. Along the lines of protein engineering, this paper reviews the progress and applications of computer-assisted protein design, and current trends and outlooks of the development.
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